wav2vec2-base-ft-keyword-spotting
This model is a fine-tuned version of microsoft/wavlm-base on the superb dataset. It achieves the following results on the evaluation set:
- Loss: 0.2270
- Accuracy: 0.9694
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3203 | 1.0 | 199 | 1.2906 | 0.6328 |
| 0.9587 | 2.0 | 399 | 0.7793 | 0.7355 |
| 0.6218 | 3.0 | 599 | 0.3858 | 0.9289 |
| 0.4379 | 4.0 | 799 | 0.2581 | 0.9688 |
| 0.3779 | 4.98 | 995 | 0.2270 | 0.9694 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.0.post302
- Datasets 2.14.5
- Tokenizers 0.13.3
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Model tree for cloudwalkerw/wav2vec2-base-ft-keyword-spotting
Base model
microsoft/wavlm-base